Direct determination of highly size-resolved turbulent ...

HAL Id: hal-00304165https://hal.archives-ouvertes.fr/hal-00304165

Submitted on 20 May 2008

HAL is a multi-disciplinary open accessarchive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come fromteaching and research institutions in France orabroad, or from public or private research centers.

L’archive ouverte pluridisciplinaire HAL, estdestinée au dépôt et à la diffusion de documentsscientifiques de niveau recherche, publiés ou non,émanant des établissements d’enseignement et derecherche français ou étrangers, des laboratoirespublics ou privés.

Direct determination of highly size-resolved turbulentparticle fluxes with the disjunct eddy covariance method

and a 12 ? stage electrical low pressure impactorA. Schmidt, O. Klemm

To cite this version:A. Schmidt, O. Klemm. Direct determination of highly size-resolved turbulent particle fluxes withthe disjunct eddy covariance method and a 12 ? stage electrical low pressure impactor. AtmosphericChemistry and Physics Discussions, European Geosciences Union, 2008, 8 (3), pp.8997-9034. �hal-00304165�

https://hal.archives-ouvertes.fr/hal-00304165

https://hal.archives-ouvertes.fr

ACPD

8, 8997–9034, 2008

Determination of

highly size-resolved

turbulent particle

fluxes by DEC

A. Schmidt and O. Klemm

Title Page

Abstract Introduction

Conclusions References

Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc

Printer-friendly Version

Interactive Discussion

Atmos. Chem. Phys. Discuss., 8, 8997–9034, 2008

www.atmos-chem-phys-discuss.net/8/8997/2008/

© Author(s) 2008. This work is distributed under

the Creative Commons Attribution 3.0 License.

AtmosphericChemistry

and PhysicsDiscussions

Direct determination of highly

size-resolved turbulent particle fluxes

with the disjunct eddy covariance method

and a 12 – stage electrical low pressure

impactor


Institute of Landscape Ecology – Climatology,University of Munster, Germany,Robert-Koch-Str. 26, 48149 Munster, Germany

Received: 8 April 2008 – Accepted: 10 April 2008 – Published: 20 May 2008

Correspondence to: A. Schmidt ([email protected])

Published by Copernicus Publications on behalf of the European Geosciences Union.

8997

http://www.atmos-chem-phys-discuss.net

http://www.atmos-chem-phys-discuss.net/8/8997/2008/acpd-8-8997-2008-print.pdf

http://www.atmos-chem-phys-discuss.net/8/8997/2008/acpd-8-8997-2008-discussion.html

http://creativecommons.org/licenses/by/3.0/

ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Abstract

During summer 2007, turbulent vertical particle fluxes were measured for a period of

98 days near the city centre of Munster in north-west Germany. For this purpose,

a valve controlled disjunct eddy covariance system was mounted at 65 m a.g.l. on

a military radio tower. The concentration values for 11 size bins with aerodynamic5

diameters (D50) from 0.03 to 10µm were measured with an electrical low pressure

impactor. After comparison with other fluxes obtained from 10 Hz measurements with

the classical eddy covariance method, the loss of information concerning high frequent

parts of the flux could be stated as negligible. The results offer an extended insight in

the turbulent atmospheric exchange of aerosol particles by highly size-resolved particle10

fluxes covering 11 size bins and show that the city of Munster acts as a relevant source

for aerosol particles.

Significant differences occur between the fluxes of the various particle size classes.

While the total particle number flux shows a pattern which is strictly correlated to the

diurnal course of the turbulence regime and the traffic intensity, the total mass flux15

exhibits a single minimum in the evening hours when coarse particles start to deposit.

As a result, a mean mass deposition of about 10 g m−2

per day was found above the

urban test site, covering the aerosol size range from 40 nm to 2.0µm. By contrast, the

half-hourly total number fluxes accumulated over the lower ELPI stages range from –

4.29×107

to +1.44×108

particles m−2

s−1

and are clearly dominated by the sub-micron20

particle fraction of the impactor stages with diameters between 40 nm and 320 nm. The

averaged number fluxes of particles with diameters between 2.0 and 6.4µm show lower

turbulent dynamics during daytime and partially remarkably high negative fluxes with

mean deposition velocities of 2×10−3

m s−1

that appear temporary during noontime

and in the evening hours.25

8998





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



1 Introduction

Particulate matter plays important roles in atmospheric processes by influencing and

driving reams of chemical reactions and trough physical interaction with the incoming

as well as the outgoing radiation. Also the formation of clouds is driven by aerosols

that function as condensation nuclei (Hatzianastassiou et al., 1998; VanReken et al.,5

2003; Seinfeld and Pandis, 2006). Furthermore, the health threats caused by aerosols

are well proven and demand further and differentiated research (e.g. Donaldson et al.,

1998; Ito et al., 2006).

Due to these extensive and partially insufficiently understood climatological and tox-

icological aspects, the measurement of aerosols in general, and the mostly turbulent10

exchange of particulate matter with the underlying surface, moved into the focus of

atmospheric research during the last several years. Many studies have focused on

the aspect of turbulent atmospheric exchange of aerosols based on vertical concen-

tration gradients, by applying the direct eddy covariance (EC) technique, or by using

various modelling approaches (Kramm and Dlugi, 1994; Petelski, 2003; Held et al.,15

2006; Martensson et al., 2006; Fratini et al., 2007; Pryor et al., 2007; Ruuskanen et al.,

2007).

Since devices for highly size-resolved particle analyses are not fast enough to mea-

sure the concentration continuously with 10 Hz (or faster) as needed for the classic EC

method, the present studies are forced to concentrate on specific compounds, or are20

constricted to specific particle size fractions. Hence, the experimental determination of

size-segregated turbulent particle fluxes is difficult and still sparsely explored. Depend-

ing on their sizes, the general properties of aerosols differ significantly in terms of their

chemical reactivity or their role concerning the radiation budget. Last but not least,

the ultrafine particles are much more harmful, concerning their influence on human’s25

health (Schwartz et al., 1996; Donaldson et al., 2002; Pope et al., 2002). Considering

that properties of aerosols, a developed understanding of size resolved particle con-

centration and transport, which occurs mostly by turbulent fluxes, is urgently needed.

8999





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Due to these actual challenges on the one hand and the reduced capability of the in-

strumentation on the other hand, the direct measurement of size-resolved turbulent

particle fluxes with the EC method has to be replaced by other approaches.

An advanced approach using fewer samples within one averaging interval is the

disjunct eddy covariance (DEC) method, originally described by Haugen (1978).5

Using the DEC method, the scalar (in our case size-resolved particle concentrations)

is measured with lower sample frequencies as limited by the response time of the

employed measurement devices.

The deviations of DEC measured scalar fluxes, compared to turbulent fluxes calcu-

lated from measurements with truly high time resolution, are within acceptable limits10

and DEC measurements still achieve the requirements of the eddy covariance theory

(Lenschow et al., 1994). Hence, as a novel and promising approach, the DEC method

can be applied for the determination of size-resolved turbulent vertical particle fluxes

directly by applying an electrical low pressure impactor (ELPI) for the size-resolved

particle concentrations as put forward by Held et al. (2007).15

The ELPI allows near real-time measurements of particle size distributions with a

time resolution of several seconds (Marjamaki et al., 2000). Within this study we ap-

plied a valve controlled DEC system for the determination of highly size-segregated

turbulent fluxes of aerosol particles, separated into 11 size classes with aerodynamic

geometric mean diameters (Di) from 40 nm through 6.4µm.20

2 Methods and materials

2.1 Site description and instrumentation

The city of Munster, with a population of about 272 000 inhabitants, is located in north-

west Germany. In contrast to the predominantly agriculturally managed surrounding,

the city itself exhibits major emissions from traffic, densely populated residential areas,25

power plants, small to medium size industrial plants, and long-range transport (Gietl et

9000





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



al., 2008; Schmidt et al., 2008). We built an experimental setup to measure the turbu-

lent exchange of particles between the urban surface and the urban boundary-layer.

The setup, consisting of a 3D-ultrasonic anemometer YOUNG 81000V (R. M. Young

Company, Traverse City, Michigan 49686, USA), an open path infrared CO2/H2O anal-

yser LI-COR 7500 (LI-COR, Inc., Lincoln, Nebraska 68504, USA), an electrical low5

pressure impactor (Outdoor ELPI, Dekati Ltd., 33700 Tampere, Finland), and a valve-

controlled particle inlet was mounted on top of a military radio tower at 65 m a.g.l. from

30 May through 6 September 2007 near the city centre of Munster. The measurement

height was about 40 m above the rooftops of the surrounding buildings. This height of

the setup ensured that the measurements were not directly influenced by single, nearby10

urban particle sources that could have disturbed the concentration measurements, but

were related to footprints that represent the city region. During the regionally predom-

inant south-westerly wind directions the tower station lies downwind of the residential

and industrial sections of the city. With respect to these main wind directions, the parti-

cle inlet, consisting of a 45 cm stainless steel capillary with an inner diameter of 3 mm,15

was mounted together with the LICOR 7500 sensor head in north-easterly direction,

close behind the measuring region of the 3D ultrasonic anemometer. Conductive sil-

icone tubing led from the steel capillary into a pinch valve box. A second conductive

silicone tubing with an in-line HEPA particle filter led to the bypass of the fast pinch

valve with a response time of 20 ms (Series 384, ASCO Scientific, Florham Park, NJ,20

USA). The valve control software which records the switching signals was also used to

record the 10 Hz wind data. Thus, by pinching either the sample tubing or the clean air

tubing, the valve was used to selectively lead either ambient sample air or particle-free

filtered air to the ELPI. With a sample flow rate of 25 l min−1

a dead volume of about 2%

of the total sample volume remained in the inlet tubing. Arranged behind a conductive25

silicone tubing with a length of 2.5 m and an inner diameter of 7.9 mm led from the

software controlled switch-valve to the ELPI on the platform directly below the mea-

surement pole as outlined in Fig. 1. At the bottom of the tower, a Laptop PC was used

to record the measurement data and to run the ELPI operational software (ELPIVI 4.0,

9001





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Dekati Ltd.) as well as the valve control software.

2.2 The electrical low pressure impactor

The ELPI allows the near-realtime measurement of airborne particle size distributions

in the size range from 7 nm through 10µm diameter, using 12 separate channels.

Within the ELPI the particles are electrically charged when passing a unipolar corona5

charger in the inlet system. Here, the particles are positively charged by colliding

with much smaller gas ions that originate from an electrical corona discharge. Af-

ter fragmentation by their aerodynamic diameter in the 12-stage cascade impactor, the

charged particles are detected in the respective stages by sensitive multi-channel elec-

trometers that register the currents as induced by the impaction of the charged particles10

on the impactor collection plates. Hence, the aerosol particles can be counted with re-

spect to their size. For this purpose, specific charger efficiency functions and kernel

functions are applied that transform the measured currents to the required values such

as particle number distributions, volume distribution, or mass distribution including all

available size classes.15

The ELPI can be run in different sensitivity modes that affect the measurement range

and the signal response time of the ELPI i.e., the shortest interval between two con-

secutive samples. During the measurements that were performed during this study,

the instrument range with a maximum current of 100 pA has been selected as tested

and recommended by Held et al. (2007). This goes with the particle concentrations at20

the urban test site and offers a response time of 4.8 s that appeared to be appropriate

for the DEC measurements. The functionality of the ELPI has already been described

within several related publications in detail (e.g. Keskinen et al., 1992; Marjamaki et al.,

2000; Baron and Willeke, 2001; Virtanen et al., 2001; Marjamaki et al., 2005). Due to

known problems of the filter stage, which tends to slightly overestimate the number par-25

ticle concentration (Pakkanen et al., 2006; Kerminen et al., 2007), only the measured

values of the 11 size bins from 0.03 through 10µm (aerodynamic cutpoint diameter

D50) were used for further calculations within this study. The analysed particle size

9002





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



bins of the ELPI are listed in Table 1.

The Di of a stage, used for the calculations of the respective mass concentrations

and therefore mass fluxes, is defined as the geometric mean given by

Din =

√

D50n · D50n+1. (1)

Here n is the stage number, Di the aerodynamic geometric mean diameter and D50n5

is the median of the aerodynamic diameter (i.e. cutpoint) of stage n.

In order to determine also the turbulent particulate mass exchange above the city

area, the expected particle density was derived from several analyses of Berner type

impactor measurements in the city area of Munster (Gietl et al., 2008). A mean particle

density of 1.5 g cm−3

can be assumed as a good approximation to be used for the10

particle mass calculations. For this purpose the stage-related particle masses were

calculated under the simplified assumption of a spherical shape with respect to the

corresponding aerodynamic geometric mean diameters of the ELPI stages (Table 1).

When calculating the mass concentrations from the current values registered by the

ELPI electrometers, the fine particle losses have to be taken into account. Due to15

diffusion, small particle sometimes impact too early on upper stages where they do

not belong and account for an adulterated increased counting of coarser particles.

Due to the cubic theoretical relation between the particle radius and its mass, this

leads to problems when obtaining the particle mass distributions. As the number of

these misclassified particles is relatively small but the mass contribution per particle of20

the upper stages is relatively large, some of the transformations from particle number

concentrations to particle mass concentrations are not reliable. The mass values are

overestimated for the coarser particle size bins above PM2.5. Therefore, size-resolved

particle mass fluxes were only obtained for the reliable range of the ELPI stages 1 to 9

(i.e. 40 nm through 2µm).25

9003





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



2.3 DEC determination of the aerosol particle fluxes

Due to the relatively slow analysis procedures for particle size distributions using an

ELPI, the determination of highly size-resolved, turbulent particle fluxes bears some

relevant problems for the application of the classical EC method with its commonly

used sampling rates in the range of 10 and 20 Hz. The DEC method offers a possi-5

bility to obtain turbulent fluxes when using slower instruments by allowing increased

measurement intervals between two samples, but keeping the sampling duration itself

short enough to capture turbulent fluctuations (Lenschow et al., 1994). In our case (as

detailed below), a measurement interval of 5 s is combined with a sampling duration of

0.4 s. The concentration scalars of the 11 particle size bins were measured simultane-10

ously by opening the pinch-valve controlled ambient air inlet every 5 seconds (∆t) for

a sampling duration of 0.4 s (ts).

The data record interval of the ELPI has been set to 1 second, which is the low-

est interval for reliable data acquisition. During the post-processing, these 1 Hz data

samples of the ELPI were summarised over the respective 5 s measurement interval15

to yield the final particle concentrations for each stage. These particle concentrations,

which were representative for the sampling duration of 0.4 s, were used to calculate

the covariance with the temporal corresponding velocity of the vertical wind compo-

nent. Thus, the DEC values were calculated with an effective time resolution of 0.2 Hz.

In combination with the short sampling time of 0.4 s these settings are still adequate to20

determine turbulent fluxes (Lenschow et al., 1994; Held et al., 2007).

2.4 Quality assessment and DEC data analysis

Concerning some statistical criteria such as the stationarity of the time series or me-

teorological restrictions, the application of the DEC method demands the same high

data quality criteria as the commonly used classic EC method. In order to test and25

assure the data quality for the flux computations, the quality criteria given by Foken et

al. (2004) and Foken (2006) were adopted. For this purpose the quality tests and data

9004





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



corrections, including coordinate rotation for the streamline fit (Wilczak et al., 2001),

consideration of density fluctuations by the WPL-correction algorithm (Webb et al.,

1980), time-lag correction by application of the maximum crosscovariance method,

stationarity check, and the calculation of the integral turbulence characteristics (ITC)

were carried out with an in-house software developed for flux time series analyses.5

A minimum friction velocity of 0.15 m s−1

, additionally applied for the verification of a

well developed turbulence regime especially during nighttime, was systematically ob-

tained with a neural network modelling-test as introduced by Schmidt et al. (2008).

Due to the position of the LICOR 7500 sensor head and the ambient air inlet, both

installed nearby the ultrasonic anemometer, the north-easterly wind direction was dis-10

turbed by the instruments. This concerned about 3% of the measurement data. The

affected data were excluded from further calculations. Furthermore, there are some

requirements concerning the ELPI particle counts.

In particular, a minimum number of registered particles is necessary, in order to gain

measurement signals that exceed the noise of the ELPI electrometers with a selected15

signal-to-noise ratio of at least 3. The respective minimum numbers are different for

each stage and were respected during data analysis by excluding values that exhibit

such low current values and therefore too low derived particle numbers.

After filtering the data set according to the described eddy covariance data require-

ments, limiting meteorological conditions, outliers, too low particle concentrations, and20

instrument malfunctions, 3500 reliable half-hour datasets containing all input variables

(i.e. temperature, wind components, CO2 concentration, water vapour concentration

and particle concentration, divided into 11 size bins) if high quality were available for

further analyses.

The used 30-min block time interval is considered to be a good compromise be-25

tween the need to cover long time series in order to catch the relevant frequencies

contributing to the flux, and the need to shorten the time series to guarantee at least

near steady-state conditions (Finnigan et al., 2003; Foken et al., 2004; Foken, 2006).

The applicability of this averaging period has also been approved for particle fluxes in

9005





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



other studies (e.g. Martensson et al., 2006; Fratini et al., 2007; Pryor et al., 2007).

The half-hourly measurement data files comprising the wind components, the (sonic)

temperature, the CO2 concentration, and the water vapour concentration contain

18 000 raw data values that were recorded with 10 Hz, whereas the half-hourly data

files of the particle concentrations contain 360 raw data values, measured with a reso-5

lution of 0.2 Hz.

In order to combine and synchronise these data for the covariance calculations, the

10 Hz wind velocity values were averaged over the ELPI sampling intervals. The av-

eraging began with the valve open signal. These averages, particularly those for the

vertical wind component w, were arranged to be perfectly synchronous to the cor-10

responding particle concentration datasets as integrated over the 0.4 s following the

opening of the ambient air inlet. Therefore, each of the resulting half-hourly averaged

particle flux values was calculated from 360 data records by using these new combined

DEC files.

During the 5 s measurement intervals, the filtered air that flowed through the system15

over 4.6 s causes no measurement signals that exceed the noise of the ELPI elec-

trometer channels. By contrast, the total current signals registered by the ELPIVI 4.0

software can be clearly recognised after opening the sample inlet (ts=0.4 s) for the

ambient air flow, every 5 s (Fig. 2).

Therefore, the total current values accumulated over all available ELPI stages offered20

a well defined adjustment signal for exact determination of the integration limits during

data analyses.

During the post-processing, the recorded “valve open” signal was used to mark the

0.4 s sampling intervals to yield the corresponding mean vertical wind velocity. Ac-

cording to Held et al. (2007), who accomplished several laboratory experiments with25

a prototype valve-controlled ELPI DEC system, the applied measurement interval of 5

seconds and the chosen sampling duration of 0.4 s appeared to be a good compromise

between the need of high resolution samples for the determination of turbulent fluxes

and the need of a reliable obtainment of the size-segregated particle concentrations

9006





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



with the ELPI.

The commonly used EC equation for the mean covariance (i.e. fluxes F ) for an aver-

aging interval of 30 min (for instance),

F30 min = c′w ′ (2)

has to be modified for our DEC application into5

F30 min =

((

5∑

i=1

ci

)

1Hz

− c30min

)

·

1

4

4∑

j=1

wj

10Hz

− w30 min

(3)

for each aerosol particle size bin. Here, c is the concentration and w is the vertical wind

velocity. The apostrophes in Eq. (2) denote the deviations of discrete measurements

from the average (e.g. of a 30-min averaging period).

Since the sampling rate is reduced in comparison the quasi-continuous 10 Hz mea-10

surements the DEC flux measurements contain an increased uncertainty. However,

the sampling rate induced flux bias, relative to the flux averages derived from 10 Hz

measurements, is negligible. This was found by Bosveld and Beljaars (2001) who ac-

complished a more detailed analysis of the effect of sampling rates on the average flux

results with respect to the theoretical backgrounds.15

The discrete sampling of continuous fluxes implies an error that can, according to

Buzorius et al. (2003), be calculated by:

δF =

√

√

√

√

√

n∑

i=1

w2ic2i

n2·

[

δ(wi )

wi

]2

+

n∑

i=1

w2ici

n2·

1

Q · ts. (4)

Here n is the number of observations per averaging interval, c the aerosol number con-

centrations, Q is the sampling flow rate, w the vertical wind component, ts the sampling20

period, and δ(w) gives the uncertainty of the ultrasonic anemometer measurements.

9007





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Hence, the first term under the square root in Eq. (4) gives the error contribution re-

lated to the wind measurements and the second term accounts for the error due to

the limited particle counting statistics. With respect to the generally lower particle con-

centrations in the upper stages the derived flux values contain higher uncertainty than

the corresponding fluxes of the smaller particle fractions. With the already described5

values used for this study, maximum errors of about 3% for the obtained fluxes of the

super-micron sizes (particle diameters >1µm) that passed the previous selected qual-

ity criteria, have to be considered.

3 Results and discussion

3.1 Comparison of fluxes originating from EC and DEC calculations10

After the necessary corrections and quality assessment procedures described in

Sect. 3.2, the covariance of w and the different particle concentrations could be ob-

tained throughout the measurement period above the city area of Munster by applying

Eq. (3). As the temporal resolution of the samples is reduced in comparison to a con-

ventional EC algorithm, the reliability and accuracy of the experimental results in form15

of the turbulent vertical fluxes need to be approved as well as possible.

For this purpose, the variables which were available with a temporal resolution of

10 Hz, namely the CO2 concentration, the wind components, water vapour concentra-

tion, and the air temperature were averaged and re-sampled by taking one 0.4 s mean

value every 5 s. Here, the valve-open marks were used to set the start points of the20

averaging intervals. Hence, we yield 0.2 Hz samples similar to the 11 simultaneous

concentrations used for the particle flux calculations.

Since 10 Hz data records were available for some variables, the fluxes of buoyancy,

carbon dioxide, and water vapour were also calculated using 18 000 raw data values

for each half-hourly turbulent vertical flux value. Hence, we were able to compare these25

synchronous half-hourly flux values calculated from the artificial 0.2 Hz DEC raw data

9008





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



values with the synchronous EC flux values calculated from the highly resolved 10 Hz

data records.

An example of the respective turbulent vertical fluxes for a several time series of

several days is shown in Fig. 3. The DEC flux values of the buoyancy flux, CO2 flux

and water vapor flux are very similar to those derived from the 10 Hz values. The DEC5

flux time series appear partially smoothed or show minor differences compared to the

corresponding EC flux values.

Hence, the loss of information concerning the high frequent parts of the turbulent

transport appears to be mostly negligible, indicating that the DEC derived flux values

can be treated as reliable in principle. Similar results concerning the correlation of the10

half-hourly average values from 10 Hz eddy covariance data and the corresponding

disjunct eddy covariance fluxes were obtained by Hendriks et al. (2008).

To obtain a quantified information about the obtained differences between the

fluxes calculated from 10 Hz measurements and the fluxes obtained with the artificial

DEC data that exhibit lower temporal resolution, the averaged percentage deviations15

δFHighLow and the roots of the mean squared errors (RMSE) are calculated over a sub-

set of 1344 half-hourly mean flux values which is equivalent to an amount of four weeks

of data with,

RMSE =

√

√

√

√

1

n·

n∑

i=1

(F Hi

− F Li

)2, (5)

and20

δFHighLow =100

n·

n∑

i=1

F Hi − F L

i

F Hi

. (6)

Here n is the number of data points, F Hi is the EC flux value calculated from the highly

temporal resolved 10 Hz measurements and F Li the corresponding DEC value, calcu-

lated from the low resolved time series of the 30-min averaging interval number i . The

9009





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



results are given in Table 2 and show a good agreement of the respective half-hourly

flux values.

Thus, it can be concluded that the DEC sampling interval is appropriate to account

for the relevant variations of the selected scalar. Furthermore, the intervals between

the samples are long enough to respect the response time of the relatively slow ELPI5

device (Held et al., 2007). The deviations show a slight underestimation of the DEC

fluxes probably due to the high frequent turbulence parts which can not be resolved

using the applied measurement interval ∆t. Overall, these results show, that fluxes as

determined with the DEC are a very good approximation of the fluxes as obtained with

the direct EC.10

3.2 Time series of size-resolved particle fluxes

Within the discussed measurement period during spring and summer 2007 the turbu-

lent vertical particle fluxes of 11 size bins were obtained by the DEC method with an

ELPI, as described above. The number fluxes are clearly dominated by the sub-micron

size bins (particle diameters <1µm) which exceed the simultaneous number fluxes of15

the super-micron size bins by orders of magnitude. The half-hourly total number fluxes

summarised over all 11 analysed ELPI stages ranging from –4.29×107

to +1.44×108

particles m−2

s−1

are dominated by the sub-micron particle fraction with diameters be-

tween 0.04 and 0.20µm.

A diurnal pattern is apparent for the aerosol number flux time series (Fig. 4). This ap-20

plies especially to the smaller size fractions (i.e. stages 1 to 6), whereas the exchange

fluxes (downward versus upward) of coarse particles (stages 10 and 11) appears to be

more or less balanced within a diurnal cycle.

To validate the supposed diurnal pattern of the particle fluxes and to justify a further

analysis of diurnal averages, a spectral analysis of the block average flux time series25

was accomplished. After fast Fourier transformation of the autocorrelation function of

the resulting total particle number flux time series (stages 1 to 11), the power spectrum

confirms a distinct diurnal pattern of the particle number fluxes. Nevertheless, power

9010





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



spectra have to be analysed carefully in order to avoid erroneous conclusions through

over-interpretation of found periodicities or even artefacts. Due to the non-evanescent

autocorrelation of the total number flux time series, the significance has to be tested

with an underlying theoretical red noise spectrum instead of a white noise background

level. Therefore, the theoretical red-noise spectrum was determined based on a mod-5

elled Markov-chain according to Gilman et al. (1963) and Priestley (1981),

SR(k) =1 − r2

1 + r2 − 2r cos(kπ/M). (7)

Here, SR are the red-noise spectrum values, M is the maximum lag of the Fourier

transformed autocorrelation function, r1 is the autocorrelation coefficient at a relative

shift of 1, and k an increasing integer value from 2 to M, corresponding to the respective10

frequency or period.

Afterwards, the theoretical Markovian spectrum can be used to determine the signif-

icance of the obtained spectrum values by a χ2– distribution test (Panofsky and Brier,

1958).

The result shows, that the 24-h peak exceeds the line marking the selected 95%15

confidence level by far (Fig. 5).

As a conclusion of the preliminary spectral significance test the 24 h – period can

be regarded as significant and meaningful in terms of the temporal behaviour of the

particle number fluxes and allows further interpretations of diurnal patterns.

Furthermore, this peak can be interpreted as validation of a relation between the20

particle flux above the urban measurement site with the diurnal pattern of the human

activities that influence the particle concentrations for example through rush-hour traf-

fic, and the meteorological conditions that drive the turbulence (e.g. temperature and

stability), both exhibiting well known and clear diurnal patterns (e.g. Martensson et al.,

2006; Schmidt et al., 2008).25

9011





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



3.3 Diurnal averages of particle number and mass fluxes

To yield reasonable daily averages in terms of statistic representativeness with simul-

taneous consideration of virtually steady seasonal conditions, the averaging interval

was chosen to include 8 consecutive weeks during July and August 2007 with similar

atmospheric conditions.5

Figure 6 shows the average diurnal total number flux and the respective accumulated

mass flux. Since the particle mass calculations are only reliable up to the sizes of

stage 9 both, the particle number fluxes and the particle mass fluxes were accumulated

over the size bins that correspond to these stages (1–9), in order to yield comparable

patterns.10

The total particle number flux exhibits a pattern with 3 peaks (about 07:30, 13:00, and

16:00 local time) that are embedded in the daily main peak that is obviously related to

the known diurnal cycle of atmospheric turbulence development (e.g. Stull, 1988; Arya,

2001).

In contrast, the averaged total particle mass flux shows lower response to the dynam-15

ics of turbulence in the daytime and increased deposition fluxes that appear temporary

in the evening.

The size-segregated average diurnal particle number fluxes (stages 1–11) are shown

in Fig. 7, while Fig. 8 shows the respective size-resolved particle mass fluxes of the

particles registered in the ELPI stages 1–9. Significant differences between the fluxes20

of the sub-micron size bins and those of the super-micron sizes can be recognized.

With regard to the fluxes of particles with aerodynamic mean diameters from 3.1 to

6.4µm (stages 10 and 11), it has to be kept in mind that, due to the relative small

particle numbers, the measured concentration values contain a greater statistical un-

certainty, which led to a reduction of the number of concentration values that passed25

the quality test and were available for flux calculations. Thus, the numbers of single

flux values which were used for the mean daily flux calculations are reduced by 9%

compared to the numbers of flux values which were available for the lower ELPI stages

9012





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



1 to 9. Nevertheless, the fluxes of the coarse particles (stages 10 and 11) were calcu-

lated from high quality data but exhibit an increased statistical uncertainty and should

be interpreted with care.

The accumulated mean fluxes of the small particle size classes of about 0.1µm

and below (stage 1 to 3) are obviously dependent on the turbulence regime. This is5

supported by the high coefficients of the Spearman rank correlation analyses with the

respective stability parameter z/L (r=–0.87) and the friction velocity u∗ (r=0.81).

Moreover, two peaks are remarkable in the diurnal course of the small particles of

stage 1 to 3 which appear in temporal correspondence with the climax of rush-hour

traffic at about 07:30 in the morning and 16:30 in the afternoon (Fig. 7a).10

In this context, the fluxes of the particles registered in stage 6 are remarkable. The

respective fluxes lead to a relevant deposition that occurs during noontime, after the

strong emission period of smaller particles during the morning rush-hour traffic.

The negative fluxes of these particles with a Di of 0.49µm can be recognised clearly

in Fig. 7b and in Fig. 8b showing its minimum at 12:00. Such observations can probably15

be explained by coagulation events and particle growth of the smaller particles, emitted

during morning rush-hour time and the deposition of the newly built and coarser parti-

cles afterwards. The mean deposition velocity of the corresponding aerosol particles

reaches its maximum of 0.21 cm s−1

during noontime at 12:00.

In spite of the much lower number contributions of the super-micron size aerosols,20

the corresponding mass fluxes show a reverse relation in terms of parts at the total

exchange. This is a consequence of the cubic relation between particle radius and

its derived mass and is amplified by the exponentially increasing differences between

the consecutive ELPI stages concerning the aerodynamic mean diameters. Thus, in

contrast to the particle number fluxes the mass fluxes are clearly dominated by the25

particles with aerodynamic diameters >0.5µm. The mostly upward direction of the

measured fluxes that belong to the lower stages 1 to 5 and the more frequent negative

fluxes of the larger aerosols (Di≥490 nm) are shown in the mean mass flux time series

(Fig. 8). Especially the turbulent mass deposition in the evening hours with respect to

9013





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



the stages 8 and 9 are notable and contribute considerably to the diurnal aerosol mass

balance.

Since the measurement site is placed in a spatially relatively homogenous area in

terms of land use within the covered footprint area, no significant differences between

particle fluxes in connection with the prevailing wind directions occurred during the 985

days of the measurement campaign.

3.4 Variations of particle fluxes related to urban activity cycles

In order to obtain precise information of the relation between traffic emissions and ur-

ban particle fluxes, the datasets were divided into two observational groups, one group

representing the weekdays from Monday through Friday, the other group representing10

Sundays and holidays, respectively. Since the traffic volume on Saturdays is some-

where in between the weekday traffic volume and Sunday traffic volume, the Saturdays

were left out of this analysis to yield clear results about the role of the traffic exhausts

concerning the turbulent particle fluxes.

A noteworthy difference between the averaged daily particle fluxes on Sundays and15

on weekdays can be obtained, particularly with regard to the accumulated particle

number fluxes of stage 1 to 3 (Fig. 9).

The decreasing fluxes after the morning rush-hour and after the second peak that

appears during the afternoon rush-hour traffic, are typical patterns of the urban particle

fluxes or other urban, mostly anthropogenic emissions such as CO2 (Velasco et al.,20

2005; Vogt et al., 2006; Martensson et al., 2006; Schmidt et al., 2008).

These characteristic temporary turbulent emission events do not occur on Sundays

or holidays. The simultaneously obtained CO2 fluxes, as measured on weekdays, ex-

hibit a diurnal course that reflects the traffic volume clearly. By contrast, the mean flux

values on Sundays show the biological net uptake by the vegetation within the city area,25

which is not strong enough to cause mean negative fluxes during the weekdays. This

provides evidence of the complex structure of atmospheric exchanges in urban areas

that are influenced by anthropogenic emissions, long range transport, and net uptake

9014





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



of CO2 by scattered vegetated areas. Due to the absence of vegetation related uptake,

the weekend fluxes of the small particles have no meaningful negative flux intervals

during noontime as the corresponding CO2 fluxes show on Sundays (Fig. 9d).

Nevertheless, since the massive temporary particle emissions from traffic do not

appear on Sundays, a similar behavior with reduced fluxes on Sundays and missing5

rush-hour peaks can be found in the diurnal cycles of the fine particles with aerody-

namic diameters between 0.04 and 0.12µm (stages 1 to 3, Fig. 9a and d). By contrast,

the coarser particles of the upper stages 4 to 6 also show a change in the amount

of flux values, but not in their relative diurnal pattern (Fig. 9b). Furthermore, aerosol

particles with diameters ranging from 0.77 to 2µm (stages 7 to 9) not even show a sig-10

nificant reduction of the amount of daily turbulent exchange on Sundays and holidays

compared to weekdays (Fig. 9c). This additionally supports the assumption that the

respective particles (stage 1 to 3) are mainly originating from the local traffic emissions

that cause this diurnal pattern in the turbulent vertical fluxes.

Thus, the reduction of the traffic amount obviously accounts for the most important15

differences in the examined urban turbulent particle exchange. As a consequence, it

can clearly be stated that the traffic pollution emission is the most important source of

the particles that belong to the size bins with geometric mean diameters ranging from

40 nm to 0.12µm (stages 1 to 3).

Similar relations between particle size to traffic volume were also found during sev-20

eral studies that focused on the composition of motor particle exhausts or related am-

bient air concentrations (e.g. Maricq et al., 1999; Harris and Maricq, 2001; Pakkanen

et al., 2006).

To determine the contributions of the single size bins at the total atmospheric ex-

change above the urban area during the measurement period without respecting the25

flux direction, the absolute values (irrespective of their signs) of the mean turbulent ex-

changes per day were accumulated for each particle size bin. The relative contributions

of these numbers to the respective totals are shown in Fig. 10.

The absolute turbulent exchange percentages confirm the special role of the particle

9015





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



size class around 0.49µm (stage 6), again. The concentration percentage and the flux

percentage exceed the expected values under the assumption of a log-linear distribu-

tion (Fig. 10). The special role of this size class has already been shown above for the

averaged diurnal fluxes as presented in Figs. 7 and 8.

Furthermore, we calculated that the ultrafine particle sizes (stages 1 and 2) account5

for 84% of the total daily number fluxes. By contrast, these particle sizes account

for a lower percentage of 66% concerning the respective daily number concentrations

during the measurement period.

In contrast to the data in Fig. 10 the values in Table 3 give the mean daily balances

through turbulent vertical fluxes with respect to the particle sizes and flux directions.10

A mean mass deposition of 9.9 mg m−2

per day was found above the urban study site

covering the particle sizes from 40 nm up to 2.0µm determined by the aerodynamic

geometric mean diameters of the ELPI stages 1–9. The direction of the obtained aver-

age fluxes shows the positive daily balance of the turbulent atmospheric exchange of

particles with aerodynamic geometric mean diameters from 40 nm to 0.32µm and the15

negative turbulent exchange balance of the coarse aerosols of stage 6 to 12 (with the

exception of stage 10).

The contribution of the particles with Di of about 0.5µm to the total deposited mass

are again emphasised by the values in Table 3 as well as the high parts of the sub-

micron particle sizes at total daily mean number fluxes.20

4 Summary and conclusion

The applied DEC method in connection with the ELPI is a relatively novel experimental

method and enabled us to obtain highly size-resolved turbulent fluxes of urban aerosols

for the first time, separated into 11 size bins. A mean positive turbulent exchange of

2.8×1013

particles per m2

per day, as summarised over all 11 size classes (40 nm to25

6.4µm), or 9.9 mg m−2

per day accumulated over the Di-range from 0.04 to 2.0µm was

obtained. The mostly positive turbulent number fluxes, measured above the city area,

9016





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



show that the city of Munster acts as a considerable source for aerosol particles.

Moreover, the results give an extended insight into the turbulent vertical particle ex-

change and show some general patterns which are clearly related to anthropogenic

activities. The different size bins show different turbulent dynamics during daytime. In

more detail, the data provide evidence for the dependencies between the turbulent par-5

ticle fluxes of the sub-micron particle sizes and traffic. The emission of small particles

and the conspicuous turbulent deposition of coarser particles during noontime exhibit

some remarkable temporal relations. The massive traffic emissions of the fine particles

with aerodynamic midpoint diameters from 40 to 120 nm (stage 1 to 3) are followed by

a correlated deposition of particles with aerodynamic diameters of 0.49µm, registered10

in the ELPI stage 6. The stable periodicity of these coherences suggests the presump-

tion that such observations can be explained by particle growth processes within the

sub-micron particle size range.

Hence, a causal relation can be assumed but needs further studies that focus on the

particle growth and the related turbulent transport to further support these conclusions.15

Furthermore, a better size-resolution, especially in the super-micron range of the PM10

fraction is an important challenge for further instrument development and future ex-

perimental research in particle flux dynamics. Also, the advanced development of the

simultaneous determination of the chemical composition of size-resolved particle sam-

ples, e.g. by application of mass-spectrometry, is necessary for the understanding of20

the atmospheric cycles of aerosols and moreover, in order to make an important step

forward in the field of particle source determination and the chemical compositions of

aerosols.

Acknowledgements. We gratefully acknowledge the Deutsche Forschungsgemeinschaft forfinancial support of this work (DFG, Kl623/8-1) and L. Harris for language editing of the25

manuscript.

We further thank T. Wrzesinsky for the development of the software applied for the wind datarecord and valve control of the DEC System. The authors also would like to thank A. Horl,S. Lieberts, M. Siewecke and P. Stein of the Manfred-von-Richthofen casern in Munster for the

9017





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



permission to use the military radio tower, and P. Sulmann for his support during the installationsat this measurement site.

References

Arya, S. P.: Introduction to Micrometeorology, Second Edition, AcademicPress, SanDiego, 420pp., 2001.5

Baron, P. A. and Willeke, K.: Aerosol Measurement – Principles, Techniques, and Applications,Second Edition, John Wiley & Sons, 1172 pp., 2001.

Bosveld, F. C. and Beljaars, A. C. M.: The impact of sampling rate on eddy-covariance fluxestimates, Agr. Forest Meteorol., 109, 39-45, 2001.

Buzorius, G., Rannik, U., Nilsson, E. D., Vesala, T., and Kulmala, M.: Analysis of dry deposition10

velocity measurement techniques for particles smaller than 100 nm, J. Aerosol Sci., 34, 747–764, 2003.

Donaldson, K., Lia, X. Y., and MacNeea, W.: Ultrafine (nanometre) particle mediated lunginjury, J. Aerosol Sci., 29, 553–560, 1998.

Donaldson, K., Brown, D., Clouter, A., Duffin, R., MacNee, W., Renwick, L., Tran, L., and Stone,15

V.: The pulmonary toxicology of ultrafine particles, J. Aerosol Med., 15, 213–220, 2002.Foken, T., Gockede, M., Mauder, M., Mahrt, L., Amiro, B. D., and Munger, J. W.: Post-field

data quality control, in: Lee, X., Massman, W., Law, B.: Handbook of Micrometeorology: AGuide for Surface Flux Measurement and Analysis, Kluwer Academic Publishers, Dordrecht,181–208, 2004.20

Foken, T.: Angewandte Meteorologie Mikrometeorologische Methoden, Second Edition,Springer, Berlin, Heidelberg, 326 pp., 2006.

Finnigan, J. J., Clement, R., Malhi, Y., Leuning, R., and Cleugh, H. A.: A re-evaluation of long-term flux measurement techniques. Part I: Averaging and coordinate rotation, Bound.-Lay.Meteorol., 107, 1–48, 2003.25

Fratini, G., Ciccioli, P., Febo, A., Forgione, A., and Valentini, R.: Size-segregated fluxes ofmineral dust from a desert area of northern China by eddy covariance, Atmos. Chem. Phys.,7, 2839–2854, 2007,http://www.atmos-chem-phys.net/7/2839/2007/.

Gietl, J. K., Tritscher, T., and Klemm, O.: Size-segregated analysis of PM10 at two sites, urban30

9018





http://www.atmos-chem-phys.net/7/2839/2007/

ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



and rural, in Munster (Germany) using five-stage Berner type impactors, Atmos. Environ.,doi:10.1016/j.atmosenv.2008.03.001, accepted, 2008.

Gilman, D. L., Fuglister, F. J., and Mitchell Jr., J. M.: On the Power Spectrum of “Red Noise”, J.Atmos. Sci., 20, 182–184, 1963.

Harris, S. J. and Maricq, M. M.: Signature size distributions for diesel and gasoline engine5

exhaust particulate matter, J. Aerosol Sci., 32, 749–764, 2001.Hatzianastassiou, N., Wobrock, W., and Flossmann, A. I.: The effect of cloud-processing of

aerosol particles on clouds and radiation, Tellus B, 50, 478–490, 1998.Haugen, D. A.: Effects of sampling rates and averaging periods on meteorological measure-

ments, Proc. Fourth Symp. on Meteorological Observations and Instrumentation, Denver,10

CO, 15–18, 1978.Held, A., Nowak, A., Wiedensohler, A., and Klemm, O.: Field measurements and size-resolved

model simulations of turbulent particle transport to a forest canopy, J. Aerosol Sci., 37, 786–798, 2006.

Held, A., Niessner, R., Bosveld, F., Wrzesinsky, T., and Klemm, O.: Evaluation and Application15

of an Electrical low pressure impactor in disjunct eddy covariance aerosol flux measure-ments, Aerosol Sci. Tech., 41, 510–519, 2007.

Hendriks, D. M. D., Dolman, A. J., van der Molen, M. K., and van Huissteden, J.: A compact andstable eddy covariance set-up for methane measurements using off-axis integrated cavityoutput spectroscopy, Atmos. Chem. Phys., 8, 431–443, 2008,20

http://www.atmos-chem-phys.net/8/431/2008/.Ito, K., Christensen, W. F., Eatough, D. J., Henry, R. C., Kim, E., Laden, F., Lall, R., Larson, T. V.,

Neas, L., Hopke, P. K., and Thurston, G. D.: PM source apportionment and health effects: 2.An investigation of intermethod variability in associations between source-apportioned fineparticle mass and daily mortality in Washington, DC, J. Expo. Sci. Env. Epid., 16, 300–310,25

2006.Kerminen, V.-M., Pakkanen, T. A., Makela, T., Hillamo, R. E., Sillanpaa, M., Ronkko T., Virtanen,

A., Keskinen, J., Pirjola, L., Hussein, T., and Hameri, K.: Development of particle numbersize distribution near a major road in Helsinki during an episodic inversion situation, Atmos.Environ., 41, 1759–1767, 2007.30

Keskinen, J., Pietarinen, K., and Lehtimaki, M.: Electrical Low Pressure Impactor, J. AerosolSci. 23, 353–360, 1992.

Kramm G. and Dlugi R.: Modelling of the Vertical Fluxes of Nitric Acid, Ammonia, and Ammo-

9019






ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



nium Nitrate, J. Atmos. Chem., 18, 319–357, 1994.Lenschow, D. H., Mann, J., and Kristensen, L.: How long is long enough when measuringfluxes and other turbulence statistics?, J. Atmos. Ocean. Tech., 11, 661–673, 1994.Marjamaki, M., Keskinen, J., Chen, D-R., and Pui, D. Y. H.: Performance Evaluation of the

Electrical Low-Pressure Impactor (ELPI), J. Aerosol Sci., 31, 249–261, 2000.5

Marjmaki, M., Lemmetty, M., and Keskinen, J.: ELPI Response and Data Reduction I: Re-sponse Functions. Aerosol Sci. Tech., 39, 575–582, 2005.

Maricq, M., Podsiadlik, D., and Chase, R.: Examination of the Size-Resolved and TransientNature of Motor Vehicle Particle Emissions, Environ. Sci. Technol., 33, 1618–1626, 1999.

Martensson, E. M., Nilsson, E. D., Buzorius, G., and Johansson C.: Eddy covariance measure-10

ments and parameterisation of traffic related particle emissions in an urban environment,Atmos. Chem. Phys., 6, 769–785, 2006,http://www.atmos-chem-phys.net/6/769/2006/.

Pakkanen, T. A., Makela, T., Hillamo, R. E., Virtanen, A., Ronkko, T., Keskinen, J., Pirjola, L.,Parviainen, H., Hussein, T., and Hameri, K.: Monitoring of black carbon and size-segregated15

particle number concentrations at 9-m and 65-m distances from a major road in Helsinki,Boreal Environ. Res., 11, 296–310, 2006.

Panofsky, H. A. and Brier, G. W.: Some Applications of Statistics to Meteorology, The Pennsyl-vania State University Press, University Park, 224 pp,1958.

Petelski, T.: Marine aerosol fluxes over open sea calculated from vertical concentration gradi-20

ents, J. Aerosol Sci., 34, 359–371, 2003.Pope III, C. A., Burnett, R. T., Thun, M. J., Calle, E. E., Krewski, D., Ito, K., and Thurston, G.

D.: Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine ParticulateAir Pollution, J. Am. Med. Assoc., 287, 1132–1141, 2002.

Priestley, M. B.: Spectral Analysis and Time Series, Vol. 1 Univariate Series, Academic Press,25

London, 1981.Pryor, S. C., Larsen, S. E., Sørensen, L. L., Barthelmie, R. J., Gronholm, T., Kulmala, M., Lau-

niainen, S., Rannik, U., and Vesala, T.: Particle fluxes over forests: Analyses of flux methodsand functional dependencies, J. Geophys. Res., 112, D07205, doi:10.1029/2006JD008066.,2007.30

Ruuskanen T. M., Kaasik M., Aalto P. P., Horrak U., Vana M., Martensson M., Yoon Y. J.,Keronen P., Mordas G., Ceburnis D., Nilsson E. D., O’Dowd C., Noppel M., Alliksaar T., IvaskJ., Sofiev M., Prank M., and Kulmala M.: Concentrations and fluxes of aerosol particles

9020






ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



during the LAPBIAT measurement campaign at Varrio field station, Atmos. Chem. Phys., 7,3683–3700, 2007,http://www.atmos-chem-phys.net/7/3683/2007/.

Schmidt, A., Wrzesinsky, T., and Klemm, O.: Gap Filling and Quality Assessment of CO2 andWater Vapour Fluxes above an Urban Area with Radial Basis Function Neural Networks.5

Bound.-Lay. Meteorol., 126, 389–413, 2008.Schwartz J, Dockery D. W., and Neas L. M.: Is daily mortality associated specifically with fine

particles?, J. Air. Waste Manage., 46, 927–939, 1996.Seinfeld J. H. and Pandis S. N.: Atmospheric Chemistry and Physics: From Air Pollution to

Climate Change, Second Edition, J. Wiley, New York, 2006.10

Stull, R. B.: An Introduction to Boundary Layer Meteorol., Dordrecht, Boston, London, KluwerAcad. Publ., 666 pp., 1988.

VanReken, T. M., Rissman, T. A., Roberts, G. C., Varutbangkul, V., Jonsson, H. H., Flagan,R. C., and Seinfeld, J. H.: Toward aerosol/cloud condensation nuclei (CCN) closure duringCRYSTAL-FACE, J. Geophys. Res., 108(D20), 4633, doi:10.1029/2003JD003582, 2003.15

Velasco, E., Pressley, S., Allwine, E., Westberg, H., and Lamb, B.: Measurements of CO2 fluxesfrom the Mexico City urban landscape, Atmos. Environ., 39,7433–7446, 2005.

Virtanen, A., Marjamaki, M., Ristimaki, J., and Keskinen, J.: Fine particle losses in electricallow-pressure impactor, J. Aerosol Sci., 32, 389–401, 2001.

Vogt, R., Christen, A., Rotach, M. W., Roth, M., and Satyanarayana, A. N. V.: Temporal dy-20

namics of CO2 fluxes and profiles over a Central European city, Theor. Appl. Climatol., 84,117–126, 2006.

Webb, E. K., Pearman, G. I., and Leuning, R.: Correction of the flux measurements for densityeffects due to heat and water vapour transfer, Q. J. Roy. Meteor. Soc., 106, 85–100, 1980.

Wilczak, J. M., Oncley, S. P., and Stage, S. A.: Sonic anemometer tilt correction algorithms,25

Bound.-Lay. Meteorol., 99, 127–150, 2001.

9021






ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Table 1. Stages of the Electric Low Pressure Impactor (ELPI) with D50 cutpoints determined bythe manufacturer and the aerodynamic geometric mean diameters Di (rounded to 2 significantdecimal places).

ELPI Stage # Aerodynamic cut-off diameter D50 (µm) Aerodynamic Di (µm)

1 0.0282 0.0402 0.0558 0.0733 0.0954 0.124 0.159 0.205 0.265 0.326 0.387 0.497 0.621 0.778 0.960 1.29 1.62 2.0

10 2.42 3.111 4.04 6.4

12 (inlet) 10.06 –

9022





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Table 2. Obtained differences between the 10 Hz EC fluxes and the respective DEC flux values.

Flux variable RMSE δFHighLow

Carbon dioxide 2.28µmol m−2

s−1

1.6%

Water vapour 0.48 mmol m−2

s−1

2.1%

Buoyancy 7.28×10−3

K m−2

s−1

0.7%

9023





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Table 3. Averaged daily turbulent particle exchange of different size bins.

Stage # Di (µm) Net turbulent mass ex-change

(mg m−2

d−1

)

Net turbulent number ex-change

(N m−2

d−1

)

1 0.040 0.69 1.36 E+132 0.073 3.25 1.06 E+133 0.12 4.89 3.61 E+124 0.20 4.02 6.40 E+115 0.32 0.18 6.87 E+096 0.49 –14.97 –1.62 E+117 0.77 –1.68 –4.69 E+098 1.2 –2.17 –1.60 E+099 2.0 –4.10 –6.50 E+0810 3.1 – 3.45 E+0811 6.4 – –3.58 E+08

9024





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Fig. 1. Schematic overview of the DEC measurement setup including the ultrasonic anemome-ter, open path CO2/H2O analyser, pinch-valve unit with sample inlet and clear air inlet, electricallow pressure impactor, and the Laptop-PC with the device control software and data acquisitionsoftware.

9025





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Fig. 2. The total current time series used for the determination of the integration limits. Thedashed line marks the accumulated electrometer noise level.

9026





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Figure 3: Continuous period of the turbulent flux time series derived from the 10 Hz EC Fig. 3. Continuous period of the turbulent flux time series derived from the 10 Hz EC measure-ments and the corresponding 0.2 Hz DEC measurements during June 2007.

9027





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Figure 4: Example of size-segregated particle number fluxes during two complete exemplaryFig. 4. Example of size-segregated particle number fluxes during two complete exemplarydays in June 2007. Note different scaling of y-axes for the four panels.

9028





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



σ

Fig. 5. Power spectrum of a continuous part of the time series containing the half-hourly totalnumber fluxes. The dashed line shows the respective 95% confidence level.

9029





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



σ

Fig. 6. Averaged diurnal aerosol number fluxes (a) and aerosol mass fluxes (b) each accumu-lated over the ELPI stages 1 to 9 (i.e. Di=0.04 to 2.0µm). The shaded area marks the ±1σdeviation, representing the day-to-day variability.

9030





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Figure 7: The mean daily particle number fluxes of the particles with Di’s from 40 nm up to

μFig. 7. The mean daily particle number fluxes of the particles with Di ’s from 40 nm up to 6.4µm.

9031





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



μFig. 8. The mean daily aerosol mass fluxes of particles with Di ranging between 40 nm and2.0µm (i.e. ELPI stages 1–9).

9032





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Fig. 9. Comparison of the averaged daily fluxes of different particle sizes (number fluxes) andcarbon dioxide on weekdays and Sundays measured during summer 2007 above the urbanstudy site.

9033





ACPD

8, 8997–9034, 2008

Determination of


turbulent particle

fluxes by DEC


Title Page



Tables Figures

◭ ◮

◭ ◮

Back Close

Full Screen / Esc



Fig. 10. Percentage contributions of the different particle sizes to the total number flux andconcentrations, respectively.

9034





Direct determination of highly size-resolved turbulent ...

Documents

Transcript of Direct determination of highly size-resolved turbulent ...